The Top Banking Fraud Types to Watch in 2024

About this white paper

A staggering five percent of corporate revenue is lost to fraud every year, totaling US$4.7 trillion globally according to the ACFE. And fraud is growing, relentlessly.

Read about the evolving tactics of fraudsters in 2024, from conventional scams to sophisticated deep fakes, and discover how cutting-edge technology like NetGuardians’ AI-driven anti-fraud systems and collaborative initiatives like Community Scoring & Intelligence Service can fortify the fight against fraud.

USE THE TABLE OF CONTENTS BELOW TO NAVIGATE THROUGH THE PAGE:

1. Introduction
2. The 2024 Fraud Landscape
2.1 Fraudulent payments initiated by authorized parties Push payment social engineering Romance scams Business email compromise Invoice fraud Investment scams Telephone scams	2.2 Fraudulent payments initiated by unauthorized parties Bank insider Phishing-enabled account takeover Man in the middle/pharming Technical support Mobile SIM swap and mobile malware
3. Conclusion

Take this guide with you

1. Introduction

The latest fraud stats make uncomfortable reading.

Fraud is growing – relentlessly.

One in four people globally have fallen victim to fraud, resulting in losses of US$1.026 trillion per year, according to the Global State of Scams 2023 report, published by the non-profit Global Anti-Scam Alliance (GASA). The report is based on survey responses from more than 49,000 people in 43 countries and revealed that almost 80 percent of respondents experienced at least one scam in the past year and 59 percent said they encountered fraud attempts at least once a month.

Sadly, GASA’s figure for overall losses does not tell the whole story – only a small percentage of frauds is reported. Mike Haley, CEO of Cifas, the UK’s fraud-prevention umbrella group, estimates that 86% of cases go unreported and the FBI puts the proportion as high as 93%. Moreover, GASA’s data cover only individual victims and their losses. The most recent Report to the Nations, a biennial research exercise by the Association of Certified Fraud Examiners (ACFE), suggested that alongside individual losses, up to five percent of corporate revenue globally is now lost to fraud every year – an estimated US$4.7 trillion.

This is partly due to pressures from the global economic downturn because crime, including fraud, tends to increase when economic conditions worsen. However, it is also getting easier to commit fraud. For those without technical computer knowledge, crime- or fraud-as-a-service (CaaS), easily found on the dark web as well as on Telegram and other messaging platforms, means software can now be rented or licensed in exactly the same way users pay for Microsoft. Ransomware packages, for example, are available for US$1,000 a month. This, too, will help drive up fraud losses throughout 2024.

But it’s not just the economic crisis and CaaS that will fuel growth. Enhanced with new and powerful tools such as generative AI, which criminal gangs are using to create text and video content to promote their scams, financial fraud has morphed into a large and well-organized global industry.

In Asia, multiple reports indicate that the huge potential proceeds from online fraud are fueling human trafficking and modern slavery. Gangs use fake job adverts to lure victims into traveling to countries such as Cambodia, Myanmar, Indonesia or Thailand where, instead of a well-paid job, they are held captive and forced to work in online ‘fraud factories’ scamming victims.

This problem has spread beyond its original centers in Asia to become a worldwide phenomenon. There is evidence that this scam is being replicated in other regions such as West Africa, where cyber-enabled financial crime is already prevalent. It is now seen as so serious that in June 2023, Interpol issued a warning Orange Notice to its members, highlighting the global threat from fraud enabled by human trafficking.

Criminals are sticking with tried-and-tested fraud types and using phone calls, text messages, emails, instant messaging and social media posts and adverts to reach potential targets. Having said that, they are proving adept at adapting their schemes to seize on changing life and work patterns to stay one step ahead, not only of law enforcement and fraud-mitigation efforts, but also of rival criminal gangs.

“WE PREDICT A RISE IN ATTEMPTS TO INSTALL MALWARE AND EFFORTS TO OVERCOME MORE ADVANCED SECURITY MEASURES.”

Phishing scams – where they try to elicit personal information such as date of birth or passwords to help them perpetrate fraud – will remain a threat in 2024. According to the US Federal Bureau of Investigation’s latest Internet Crime Report, phishing remains the biggest single fraud type reported in the US, but individual losses were relatively small, totaling US$52 million. However, a much smaller number of investment frauds, often involving cryptocurrency schemes, led to US$3.3 billion of losses, the FBI reported.

Love, investment and delivery scams, as well as deepfakes, will continue to feature throughout 2024, as we discuss in a recent blog article. In addition, we expect to see more fraud where criminals try to impersonate work colleagues in emails, not only within companies but also in public bodies and institutions. This is a growing trend thanks to the increase in staff working from home following the pandemic and using less secure computer networks.

We also predict a rise in attempts to install malware and efforts to overcome more advanced security measures such as two-factor authentication, as well as touch or face identification. Mobile-phone SIM swaps, which we first saw in Africa, have become a growing problem elsewhere, while in Asia-Pacific mobile malware such as FluHorse and Nexus is spreading very rapidly and infiltrating smartphones worldwide. These programs are primarily engineered for credential harvesting, extracting banking and card details and obtaining SMS/Authenticator two-factor authentication codes. The information harvested enables everything from identity theft to account takeover.

As mobile banking and payments continue to rise, so will fraud. Indeed, our ever-larger digital footprints will continue to extend the potential attack surface, making identity theft as a result of hacks more likely. We will also see a further increase in ‘quishing’, where criminals use malicious QR codes to redirect users to fake websites or manipulate payments.

Thankfully, just as criminals use technology to try to commit fraud, so companies continue to develop technology that prevents it. Use of advanced software for real-time monitoring and fraud prevention is receiving additional impetus from the developing regulatory situation, which is tending to divide liability for scams between the banks that send and receive fraudulent payments. The UK Payment System Regulator’s liability model provides a recent example of this sharing of responsibility for addressing fraud.

We predict that 2024 will see further development of systems that use artificial intelligence and machine learning to spot and stop fraud without adding friction for the user. Software built specifically for banks that learns over time is proving an indispensable line of defense in the fight against fraudsters. Sharing information about frauds through initiatives such as NetGuardians’ Community Scoring & Intelligence program will also become ever-more important in the battle against the criminals.

As the threat continues to grow, so will demand from banks and their stakeholders for these effective fraud-management solutions. 2024 won’t be an open season for fraudsters as far as companies like NetGuardians are concerned.

2. The 2024 Fraud Landscape

Our survey of the 2024 payment fraud landscape follows the Fraud Classifier model produced by the US Federal Reserve’s FedPayments Improvement program. This groups fraud types according to who initiates the payment – an authorized or unauthorized party. Both types tend to involve a combination of technology tools and efforts to manipulate and dupe the victim.

However, in almost all cases, the fraud is executed by initiating payments or withdrawals from victims’ accounts that are not consistent with their normal patterns of behavior. This is the weakness in such fraud attempts that enables NetGuardians’ AI software to identify and prevent them.

Authorized frauds

1. Push payment social engineering

2. Romance scams

3. Business email compromise

4. Invoice fraud

5. Investment scams

6. Telephone scams

Unauthorized frauds

1. Bank insider

2. Phishing-enabled account takeover

3. Man in the middle/pharming

4. Technical support

5. Mobile SIM swap and mobile malware

All these frauds are frequently accompanied by money muling, whereby the stolen money is paid to someone who agrees to receive the funds and pass them on for a fee, as part of the money-laundering process. This saves the criminal organizations from having to send the funds overseas to be laundered. Instead, the funds are split and put through individuals’ accounts in amounts small enough not to trigger the bank’s minimum threshold for a suspect transaction alert.

Money muling is widespread, especially among digitally orientated banks. In the UK, young people are most likely to be targeted by fraudsters as potential money mules. In late 2022, Lloyds Bank reported that around half the money laundered in the UK passed through bank accounts belonging to people under the age of 24.

In June 2023, Europol said: “More than 90 percent of money mule transactions identified through European Money Mule Action are linked to cybercrime. The illegal money often comes from criminal activities like phishing, malware attacks, online auction fraud, e-commerce fraud, business email compromise (BEC) and CEO fraud, romance scams, holiday fraud (booking fraud) and many others.”

NetGuardians Community Scoring & Intelligence solution enables banks to receive alerts containing anonymized and encrypted information from other banks that use this software about accounts involved in money laundering. This community insight is fed back into the banks’ models in real time, helping to refine the risk scoring for every transaction that goes through each bank.

2.1 Fraudulent payments initiated by authorized parties

2.1.1 Authorized push payment fraud resulting from social engineering

Social engineering and simple telephone impersonation techniques can also be used to dupe victims into making payments to accounts controlled by the fraudsters themselves.

For example, victims may be told that their account has been compromised and they must transfer their money to a new account to prevent it from being stolen.

APP (authorized push payment) is a major source of losses due to fraud globally. It accounts for the majority of frauds recorded in Asia-Pacific, usually enabled by social engineering and impersonation. In the UK, cases of APP fraud increased by 22 percent in the first half of 2023 compared with the same time in 2022, according to UK Finance. UK consumers suffered gross losses to APP of £485 million during 2022, and another £239.3 million in the first half of 2023. The Federal Trade Commission reported in February 2023 that American consumers lost US$2.6 billion to imposter scams in 2022, up from more than US$2.3 billion the previous year.

Although by its nature quite simple, APP is one of the most difficult fraud types to detect because so many features of the transaction – customer log-in, device and session information – would be exactly the same as if the payment were legitimate. This places greater stress on the effectiveness of risk indicators linked to the beneficiary account, such as its geographic location and whether the victim has made a payment to this account before. However, NetGuardians’ solution has proved that it can detect and prevent APP fraud, which in 2022 accounted for 94 percent of the frauds detected at financial institutions using NetGuardians software.

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Case study: Authorized push payment fraud

Using impersonation techniques, the fraudster convinced the bank customer to transfer €125,000 to an illicit account in Spain.

Solution: NetGuardians’ AI-based fraud detection solution blocked the transaction because certain variables did not match the customer’s profile, including the date the transfer was initiated, the destination country, beneficiary account, order type and currency.

Case study: Romance scam

The fraudster introduced himself to the victim as an American soldier based in the Middle East. A romantic relationship began and the fraudster convinced the victim to make three transfers to his bank in Germany – of US$1,500, €3,000 and €11,300.

Solution: NetGuardians’ AI risk models stopped the first and third transactions, spotting unusual variables, including the beneficiary bank account, the destination country, the amount and currency.

2.1.2 Romance scams

Romance scams until recently tended to involve the victim being approached via text message, email or social media and convinced to begin a long-distance relationship. But recently, AI-powered image-generation software is being used to make video calls to victims using deepfake video feeds.

AI programs allow fraudsters to upload a still photograph which is animated.

The scammer can then speak to the victim on a video call, using the appearance of the person in the still photo. The generative AI software animates the deepfake image so the scammer can look into their video camera and the victim will see the deepfake avatar saying their words and reproducing their facial expressions in real time.

Once the victim is drawn in, the fraudster requests money transfers to allow them to come to the victim’s country, clear debts or unlock a frozen bank account. In one recent case reported in the UK, a woman in her fifties lost £350,000 after deepfake video calls during which the fraudster asked her to marry him. She withdrew money from her pension early after he told her that he was being held hostage and tortured by because he owed money.

Sadly, even after attempted romance frauds are flagged up by their bank, victims often insist on authorizing the payments. This demonstrates the power of romance scams to dupe victims, who want to believe they have found a genuine relationship. Banks need to be able to show victims that the payment is going somewhere other than what the victim has been told.

Isolation brought on by measures taken to stop the spread of Covid-19 appears to be behind a sharp jump in romance scams. According to UK Finance, the UK’s banking trade body, the number of romance scams increased by 29 percent between the first half of 2022 and the same period in 2023. Losses grew by 26 percent over that period to £18.5 million.

2.1.3 Business email compromise (BEC)

Fraudsters frequently target companies by impersonating a senior executive. An email is sent to an employee, either from the victim’s own email account, which has been hacked, or from a spoofed email address. The email is often followed by a call apparently from the CEO, a senior executive, or from a bogus law firm or consultant, telling the employee who received the email to respond immediately. Deep fakes are increasingly used for video or voice calls. The email usually requests a large payment to a fake account in connection with an urgent or sensitive issue such as an acquisition.

Some 73% of companies fall victim to BEC fraud every year. The latest figures from the FBI show BEC scams in the US led to losses of more than US$2.7 billion in 2022, from some 21,800 reported cases. Since 2016, BEC frauds have cost organizations some US$43.3 billion.

Case study: CEO fraud

A fraudster impersonated the CEO of a Spanish company and over email convinced an employee to transfer €170,000 to an illicit account.

Case study: BEC fraud

The victim received an email from their business partner’s email account, which had been hacked, requesting a transfer of US$100,000 to an account in Peru.

Solution: In both cases, NetGuardians’ AI-based fraud detection solution blocked the transactions due to the unusual variables the transactions exhibited, including the beneficiary account details, destination country, operation type, order type and currency.

Case study: Invoice fraud

A company received an invoice for US$69,000 payable to a previously unknown account in Singapore. The Singapore-based beneficiary’s name was similar to the name of an existing supplier based in Hong Kong. The IBAN shown on the fake invoice had been modified.

Solution: NetGuardians’ solution detected and blocked the fraud due to the unusual amount, destination country and bank.

2.1.4 Invoice frauds

Invoices purporting to come from a genuine supplier are emailed to the company, along with fake account details for payment. This type of fraud can cause major problems for smaller companies that lack the controls to prevent them and rely on non-specialist, junior staff to make payments.

2.1.5 Investment scams

The number of individuals investing online has grown strongly since the Covid-19 pandemic, partly due to home working. In response, gangs have set up fake investment websites to fool people looking to invest in stocks, commodities and cryptocurrencies. The sites are marketed to victims using phishing emails and online adverts on social media sites. Like romance scams, investment scams have become much more prevalent in Asia-Pacific recently.

The FBI’s Internet Crime Complaint Center reports that in 2022, the most recent full year for which data is available, around US$3.3billion was lost to investment scams in the US. In the UK, according to UK Finance, victims reported losses of more than £114 million during 2022 and a further £57.2 million in the first six months of 2023.

Case study: Investment fraud

The victim was advised by a fraudster impersonating a business partner to invest in a fictitious company and ordered a payment of US$170,000 to an account at a bank in Bulgaria.

Solution: The fraud detection solution blocked the payment because several variables did not match the victim’s profile, including the unusual destination country, bank, beneficiary account, amount and currency.

Case study: Account takeover

A fraudster impersonating a bank employee persuaded a customer to disclose their e-banking login details through social engineering. The fraudster then took over the account and attempted to transfer £21,000 to an illicit account.

Solution: NetGuardians’ AI-based fraud detection solution blocked the transaction due to unusual e-banking and transaction characteristics, including the unusual amount, the use of a previously unknown device just after the customer’s SIM card had been swapped, screen resolution, beneficiary bank and account details, e-banking session language and currency.

2.1.6 Social engineering and telephone scams

Even well-known, unsophisticated techniques such as telephone frauds, or ‘vishing’, which date back decades, continue to be extremely effective, especially when combined with basic social engineering using information about the victim that is easily found online.

This type of scam can involve callers pretending to be agents working for a wide variety of organizations, such as the victim’s bank or the tax authorities. Victims are persuaded to disclose their banking credentials, allowing the criminals to take control of their account.

Cifas says in its 2023 Fraudscape report25 that 64 percent of account takeover cases originate through online channels and 26 percent via telephone. The most popular uses for stolen banking details are online retailers and mobile telecoms providers. Most victims are aged 41 or above.

Gangs have set up fake investment websites to fool people looking to invest in stocks, commodities and cryptocurrencies.

2.2 Fraudulent payments initiated by unauthorized parties

2.2.1 Bank insider frauds

Insiders can be bank employees or staff employed by IT vendors working with the bank. Because these people have detailed knowledge of the bank’s internal systems, this fraud can be difficult to detect and can continue for long periods unless a robust fraud-monitoring system is in place.

Insiders exploit user privileges to access victims’ accounts directly, share customer information with fraudsters or transfer funds from the bank’s internal payment and settlement accounts into accounts belonging to customers. The funds are then transferred to external accounts controlled by the fraudster or to pre-paid cards. These types of cards are popular with fraudsters because they are issued with minimal ‘know your customer’ (KYC) checks and can be used to make multiple currency cash withdrawals. Recently we have seen a trend in which bank staff with privileged access collude with colleagues engaged in fraud to help them falsify their audit trail.

In its report Occupational Fraud 2022, A report to the nations, the Association of Certified Fraud Examiners found that banking and financial services was one of the top three sectors affected by internal fraud, with the average loss at US$100,000.

Case study: Privileged user abuse

An IT administrator at a bank in Tanzania took advantage of backend user privileges to inflate account balances for an accomplice by a total of US$22,000. The intention was to withdraw the funds from ATMs and via mobile banking, but the fraud was detected and money never left the bank.

Solution: NetGuardians’ AI-based solution detected that the privileged user checked the accomplice’s account several times over a period of days and flagged the behavior as suspicious.

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Case study: Phishing-enabled account takeover

A fraudster used phishing to introduce malicious code into the Swiss victim’s computer and acquired their e-banking credentials. The criminal then took over the victim’s account and attempted to make an illicit transfer of CHF19,990.

Solution: NetGuardians stopped the payment as several factors did not match the customer’s profile, including the size of the transfer, the new beneficiary and bank account used, as well as the unfamiliar screen resolution and browser used by the fraudster.

2.2.2 Phishing scams

Millions of fake official emails or text messages from banks, companies, delivery agents, tax authorities, health services and many other sources are sent every day. The emails contain links that, once clicked by an unwary victim, automatically download and install a piece of malware on their device which gathers personal information needed for an account takeover. We expect generative AI to become an important enabler of these kinds of fraud in 2024.

According to the Anti-Phishing Working Group, the number of unique phishing sites detected worldwide rose from 165,772 in Q1 2020 to 1.35 million at the beginning of 2023. According to Verizon’s 2023 Data Breach Investigation Report, phishing was implicated in 36 percent of all data breaches.

The UK’s National Westminster Bank reported in October 2023 that some 37 percent of UK adults had been targeted by phishing scams during the previous 12 months.

2.2.3 Man in the middle/pharming scams

A hacker obtains sensitive information transmitted between two other parties online. This can happen when the victim is intercepted trying to log in to their online or mobile banking service, allowing their log-in information to be harvested.

Case study: Man in the middle scam uses fake QR code

A client wanted to access her e-banking service. After entering her credentials and scanning the QR code, a message appeared in French and German asking her to re-enter her credentials for greater security. After she did so, an error message appeared saying the site was unavailable. This is likely to have been a man in the middle attack in which the second QR code was displayed by a hacker to recover the victim’s account credentials. The fraudster then attempted a payment of CHF38,000.

Solution: NetGuardians blocked the payment due to unusual session information, including browser language and screen resolution, and transaction details including the unusual amount and beneficiary bank. The system logs showed three sessions that raised suspicions, suggesting the fraudster accessed the victim’s account several times while attempting the payment.

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Case study: Technical support scam

The fraudster impersonated a Microsoft tech support worker and called the victim. Through social engineering, the perpetrator managed to obtain enough information about the victim’s e-banking credentials to attempt to transfer US$7,500 to an illicit account in Lithuania.

Solution: NetGuardians’ AI risk models stopped the transaction because its features did not match the customer’s profile, including the unusual currency, type of transaction, beneficiary account details and country of destination.

2.2.4 Invoice frauds

4. Technical support scam
Fake technical support staff call the victim, who is told there is a problem with their software. The victim is duped into giving the caller control of their computer remotely, sometimes with the help of personal information about them gathered via social engineering. The fraudster is then able to gain access to their computer and steal confidential information. Alternat-ively, the victim receives an email or is invited to click on a pop-up window.

According to the US Federal Bureau of Investigation’s latest Internet Crime Report, more than 32,500 people in the US reported falling for a technical support scam in 2022. Losses total more than US$806 million – an increase of 132 percent year-on-year. Older people are the main target of this type of fraud, says the FBI, with victims aged 60-plus accounting for US$724 million of the overall loss.

2.2.5 Mobile SIM-swap and mobile malware frauds

Stealing mobile numbers via SIM swap is spreading rapidly in Europe and remains a key fraud vector in Africa, because the primary way most people access mobile banking is via their mobile phone number. Their mobile number is connected to their bank account and used to verify their identity – most banks also use this phone number as a primary 2FA implementation mechanism.

The victim receives a call from a fraudster pretending to represent a telco to check account details. Using the personal information obtained, the fraudster poses as the victim and contacts their mobile service provider to have their number transferred to a new SIM in a device the gang controls. This gives access to the victim’s mobile wallet and can even allow the fraudster to attempt to reset the victim’s mobile banking security data and access their account. In other cases, gangs work with insiders at telco sales teams to obtain replacement SIMs for ‘lost phones.’

In Asia-Pacific the use of mobile malware that victims are tricked into downloading to their smartphone is also spreading very fast.
According to the FBI, SIM swaps netted fraudsters US$72 million in 2022 in the US. This compares with US$12 million between 2018 and 2020. In one SIM-swap case in Dubai, a court recently ordered a bank to pay one victim Dh9.5 million (US$2.5 million) after the victim lost that amount to fraudsters.

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Case study: M-wallet fraud in Africa

In one recent case reported in Kenya35, a gang targeted well-off people who had recently died, aiming to cancel and swap their SIM to a new device before their family had the chance to access the deceased person’s bank account and establish their exact wealth. Once the SIM was transferred, the victim’s mobile wallet was emptied and the funds transferred to other wallets, from where it was withdrawn.

Solution: NetGuardians’ fraud detection solution can spot and prevent attempts to withdraw funds stolen during this type of fraud. Repeated visits to the same ATM in quick succession raises an alert in real time, enabling the bank to check whether or not the attempted withdrawals are legitimate. NetGuardians’ software uses a ‘deceased flag’ in its models, which boosts the risk score ascribed to transactions that originate from the account of someone who is dead.

Even well-known, unsophisticated techniques such as telephone frauds continue to be extremely effective, especially when combined with social engineering

3. Conclusion

Banking frauds are constantly shifting as criminals find effective ways to get past their victims’ defenses. During the Covid-19 pandemic, for example, the huge rise in home delivery of goods during lockdowns created a new line of attack for fraudsters. Text messages purporting to come from Amazon invited people to click on a link to obtain a refund. The current increase in the cost of living means the public is often tempted by great deals on popular online marketplaces – these bargains are often scams and turn out to be ‘goods never delivered’ fraud.

Fraudsters will ‘follow the money’ and move to channels where the number of potential victims is increasing.

No matter how mechanisms for executing the fraud change shape, however, they will still rely for their success on the same basic aspects of human psychology. Fraudsters will succeed, as they always have, by exploiting their victims’ fear, anxiety and readiness to trust messages that appear to come from official sources.

Banking fraud continues to increase and the question of who is liable for the losses that result is becoming a more serious concern. Banks are generally liable to reimburse victims of frauds in which the fraudster initiates the illicit payment. In cases where the victim does so – authorized push payment frauds – banks have usually been able to avoid liability.

This is changing, however. In the UK, more than 300 institutions, including the 10 leading banks, have voluntarily signed up to the Contingent Reimbursement Model Code, which allows individuals, micro-enterprises and charities that become victims of authorized push payment fraud to claim reimbursement from their bank – unless the victim was warned about the potential for scams before making the payment but chose to go ahead. This greatly increases the banks’ exposure to fraud risks and makes it even more important for them to take effective real-time prevention measures that will allow suspect transactions to be blocked and validated.

Regulations drawn up by the UK’s Payment Systems Regulator that split fraud liability equally between sending and receiving banks will come into force in 2024, setting a precedent that is likely to be repeated in many jurisdictions. In Europe, the same model will be adopted under the third Payment Services Directive, while elsewhere, including Australia and the US, banks are facing calls to offer consumers better protection against scams. This is likely to increase demand for systems that can detect and stop fraudulent payments before they leave the customer’s account, such as NetGuardians’ AI-based anti-fraud solution.

Although a wide variety of banking frauds are commonly attempted, there is only one reliable way to detect and prevent them: comparing the fraudulent transaction against the historical pattern of behavior associated with the account holder or system user. This is why in creating solutions it is critical to focus not on the different types of fraud but on the usual behavior of the account holders, so that anomalies can be detected and flagged.

Anomalies and behavioral models

NetGuardians’ system carries out checks on transactions across multiple axes. It tracks unusual access to the bank’s internal systems and monitors internal users’ payments where these are linked to suspect transactions.

The software also uses behavioral models to identify unusual activity on customers’ accounts that may indicate account takeover. Triggers may include the detection of a different screen resolution than the one expected on the login device, a login from a new device or a previously unknown location, a login from an unknown browser or use of a different language. ‘Velocity models’ are employed to flag heightened activity on customer accounts, for example when multiple transactions are initiated in quick succession, which may indicate an attempt to empty the account as quickly as possible.

Reducing false alerts and operational losses

NetGuardians’ solutions produce impressive results: a reduction of up to 85 percent in false-positive alerts, a reduction of up to 93 percent in time spent investigating fraud and a more than 75 percent cut in operating costs related to fraud mitigation.

Machine learning algorithms dramatically reduce rates of false positive alerts, delivering a better detection rate, and avoiding the negative impact on customer satisfaction of interrupted transactions and unnecessary call-backs.

Ultimately, this approach of continually refining the machine-learning algorithms is the only practical solution to protecting customers, eliminating false positives and stopping emerging types of fraud that would otherwise be extremely difficult to detect.

Collaborative approach to fighting fraud

NetGuardians’ Community Scoring & Intelligence solution is not only a powerful tool but also the ultimate way to better fight fraud effectively. The solution enables banks to share information on frauds in a secure and anonymized way, further bolstering their defenses. Banks that use this solution generate and share encrypted alerts safely with other banks that are part of the community, highlighting new fraud methods and flagging accounts involved in muling and money laundering. The insight that is shared is then incorporated into all the member-banks’ risk models, allowing them to improve their transaction monitoring.

Yes, fraud is growing, but in response to this escalating threat, collaborative measures are essential. Together, in collaboration with financial institutions like yours, we stand united in the fight against fraud, safeguarding the assets of individuals and institutions while ensuring the integrity of our financial systems. #TogetherWeFightFraud